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Record W34402520 · doi:10.1093/rpd/ncab120

海岸複合地形における砂丘上村落の農業開拓( 20世紀メコン・デルタの開拓)

2001· article· en· W34402520 on OpenAlexfundno aff
洋子 高田

Bibliographic record

Venue東南アジア研究 · 2001
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBusiness

Abstract

fetched live from OpenAlex

Living systems have evolved in the presence of naturally occurring ionising radiation. REPAIR is a research project investigating the biological effects of sub-natural background radiation exposure in SNOLAB, a deep-underground laboratory. Biological systems are being cultured within a sub-background environment as well as two control locations (underground and surface). A comprehensive dosimetric analysis was performed. GEANT4 simulation was used to characterise the contribution from gamma, muons and neutrons. Additionally, dose rates from radon, 40K and 14C were calculated based on measured activity concentrations. The total absorbed dose rate in the sub-background environment was 27 times lower than the surface control, at 2.48 ± 0.20 nGy hr-1, including a >400-fold reduction in the high linear energy transfer components. This modelling quantitatively confirms that the environment within SNOLAB provides a substantially reduced background radiation dose rate, thereby setting the stage for future sub-background biological studies using a variety of model organisms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.204
GPT teacher head0.490
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

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